A promising prognostic signature for lung adenocarcinoma (LUAD) patients basing on 6 hypoxia-related genes.
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ABSTRACT: Background
Hypoxia signaling plays a critical role in the development of lung adenocarcinoma (LUAD). We herein aimed to explore the prognostic value of hypoxia-related genes and construct the hypoxia-related prognostic signature for LUAD patients.Methods
A total of 26 hypoxia-related genes were collected. Five hundred thirteen and 246 LUAD samples were obtained from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Univariate Cox regression and LASSO Cox regression analyses were conducted to screen the hypoxia-related genes associated with the prognosis of LUAD patients, which would be used for constructing prognosis predictive model for LUAD patients. Multivariate Cox regression analysis was done to determine the independent prognostic factors. The Nomogram model was constructed to predict the prognosis of LUAD patients.Results
Based on 26 hypoxia-related genes, LUAD samples could be divided into 4 clusters with different prognoses. Among which, 6 genes were included to construct the Risk Score and the LUAD patients with higher Risk Score had worse prognosis. Besides, the Nomogram based on all the independent risk factors could relatively reliably predict the survival probability. And 9 types of immune cells' infiltration was significantly differential between high and low risk LUAD patients.Conclusion
The Risk Score model based on the 6 crucial hypoxia-related genes could relatively reliably predict the prognosis of LUAD patients.
SUBMITTER: Luo J
PROVIDER: S-EPMC8677978 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSearching for immunotherapy-related markers is an important research content to screen for target populations suitable for immunotherapy. Prognosis-related genes in early stage lung cancer may also affect the tumor immune microenvironment, which in turn affects immunotherapy.ResultsWe analyzed the differential genes affecting lung cancer patients receiving immunotherapy through the Cancer Treatment Response gene signature DataBase (CTR-DB), and set a threshold to obtain a total of 176 differential genes between response and non-response to immunotherapy. Functional enrichment analysis found that these differential genes were mainly involved in immune regulation-related pathways. The early-stage lung adenocarcinoma (LUAD) prognostic model was constructed through the cancer genome atlas (TCGA) database, and three target genes (MMP12, NFE2, HOXC8) were screened to calculate the risk score of early-stage LUAD. The receiver operating characteristic (ROC) curve indicated that the model had good prognostic value, and the validation set (GSE50081, GSE11969 and GSE42127) from the gene expression omnibus (GEO) analysis indicated that the model had good stability, and the risk score was correlated with immune infiltrations to varying degrees. Multi-type survival analysis and immune infiltration analysis revealed that the transcriptome, methylation and the copy number variation (CNV) levels of the three genes were correlated with patient prognosis and some tumor microenvironment (TME) components. Drug sensitivity analysis found that the three genes may affect some anti-tumor drugs. The mRNA expression of immune checkpoint-related genes showed significant differences between the high and low group of the three genes, and there may be a mutual regulatory network between immune checkpoint-related genes and target genes. Tumor immune dysfunction and exclusion (TIDE) analysis found that three genes were associated with immunotherapy response and maybe the potential predictors to immunotherapy, consistent with the CTR-DB database analysis.ConclusionsFrom the perspective of data mining, this study suggests that MMP12, NFE2, and HOXC8 may be involved in tumor immune regulation and affect immunotherapy. They are expected to become markers of immunotherapy and are worthy of further experimental research.
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